Decoupling People and Processes

McKinsey & Company just published a very interesting short review of machine learning and speculate on whether advances in machine learning will result in productivity rising while employment does not. See: www.mckinsey.com/insights/public_sector/the_great_decoupling?p=1

Historically, the Industrial Revolution has led to automation and increased productivity. People displaced when one industry is automated move to new jobs created by new industries. The growth generated by every greater productivity (cheaper products) keeps the who thing going. In 1775, when the Industrial Revolution began, and only recently in China, the majority of the people in a country worked in agriculture. Today, in the US, only something like 2% of the population work on farms and manage to produce all the food we need. The rest of the population, most of who used to work on farms, now work in manufacturing or in service industries. And, since the early years of the 20th Century, the percent of the US population working in manufacturing has also been declining. Today most people work in service jobs. This pattern has been so consistent over the course of the last 200 years that many think it will always be the case.

Recently, however, computers have made it possible to do more and more jobs that were previously thought to be human jobs. Indeed, new computer software is making it possible to automate many tasks within the service industries. They are managing sales online, making business decisions, and writing music for movies. In other words we are now automating more and more jobs, and some are concerned that we will someday automate almost all jobs. That would result in a huge increase in productivity, and a huge drop in the cost of goods and services. And the economy would collapse, since there would be no employed people left with the money to buy any of the increadably cheap goods and services being created by the machines.

There is some data to support this idea. The recovery from the 2008 collapse is now underway, and while business is humming again, there are still lots of people out of work. It's a little hard to judge this data, as outsourcing and the productivity of China has thrown all US data off a little, but it seems that the rate at which people are redeployed to new jobs, as old jobs are automated, is declining.

An economist in the McKinsey article suggests “livelihood insurance.” However its done, it seems that if we keep accelerating the rate at which we automate, we will need to find a way to transfer money to those who are displaced so that they will continue to have purchasing power, even after they are displaced. It's hard to imagine the political changes that would be required to facilitate such a solution, but that's a problem for people living a few decades from now.

Today, process practitioners need to consider that there will likely be growing resistance to automation as people see themselves being replaced with less and less like hood of new employment.